探索系统性审查的特点,方法和报告,并对时间到事件结果进行元分析:一项元流行病学研究
Marius Goldkuhle1, Caroline Hirsch2, Claire Iannizzi2
1Institute of Public Health, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Str. 62, 50937, Cologne, Germany. marius.goldkuhle@uk-koeln.de.
BMC medical research methodology
|November 26, 2024
概括
在系统审查中报告时间到事件分析是不一致的,反映了初级研究中的问题. 需要改进报告标准,以便准确地对时间到事件结果进行元分析.
科学领域:
- 生物统计学 生物统计学
- 临床流行病学临床流行病学
- 医学研究综合 医学研究综合
背景情况:
- 时间到事件分析带来了方法上的挑战.
- 之前的研究强调了随机试验出版物中报告缺陷.
- 这些问题使得使用聚合数据对时间到事件结果的元分析变得复杂.
研究的目的:
- 检查包括时间到事件分析的系统审查的特征,报告和方法.
- 确定临床试验中合成时间到事件数据的常见做法和局限性.
主要方法:
- 从2017年2月至2020年8月对科克伦评论和核心临床期刊 (Medline) 进行系统搜索.
- 确定了50个基于危险比率 (HR) 的元分析和50个相应的随机试验的Cochrane评论.
- 重复数据提取侧重于结果定义,一般和时间到事件特定的方法,以及处理相关的试验特征.
主要成果:
- 分析了217个时间到事件的结果,最常见的是整体存活率 (41%).
- 结果定义 (48%) 和一般方法 (例如,分析类型,效果估计调整) 报告不足.
- 事件发生的关键时间特征 (例如,可变后续,审查,比例危险) 很少被报告;绝对影响估计经常被误算或错误标记.
结论:
- 在临床试验层面报告时间到事件分析的局限性在系统审查层面仍然存在.
- 在对时间到事件结果的元分析中,不一致的报告实践凸显了加强报告标准的必要性.
相关概念视频
01:20Comparing the Survival Analysis of Two or More Groups
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Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
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01:18Introduction To Survival Analysis
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01:15Assumptions of Survival Analysis
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01:24Kaplan-Meier Approach
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01:21Cancer Survival Analysis
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01:12Hazard Ratio
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The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
For example, in a clinical trial...
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